Key result
Predicted visceral adipose tissue equations explain more variance in inflammatory biomarkers than anthropometric measures.
Why the study?
Visceral adipose tissue (VAT) and low-grade systemic inflammation are linked to chronic conditions, and equations exist to estimate VAT, but their relationships with inflammatory biomarkers needed comparison.
Do predicted visceral adipose tissue equations better correlate with biomarkers of chronic inflammation compared to standard anthropometric measures in adults aged 46-73 years?
Cross-Sectional (n=2,038)
Do predicted visceral adipose tissue equations better correlate with biomarkers of chronic inflammation compared to standard anthropometric measures in adults aged 46-73 years?
Predicted visceral adipose tissue equations may be more useful than standard anthropometric measures for characterizing metabolic health and systemic inflammation.
May support predicted VAT equations over anthropometrics for inflammation assessment; hypothesis-generating, prospective validation needed before clinical use.
Background Evidence has linked low‐grade systemic inflammation and visceral adipose tissue (VAT) with development of chronic conditions. Cytokines and select proteins released by VAT may promote a low‐grade inflammatory response. A number of equations have been developed to estimate VAT levels. In this study, we compared predicted VAT equation relationships with biomarkers of inflammation. Methods This was a cross‐sectional study of 2038 men and women aged 46–73 years. Correlation and linear regression analyses were performed to examine inflammatory biomarker relationships with four commonly assessed anthropometric measures and 10 predicted VAT equations. Results Compared with anthropometric measures, predicted VAT equations were found to explain a greater proportion of variance in CRP ( R 2 = .075, p = .001), IL‐6 ( R 2 = .060, p = .001), TNF‐α ( R 2 = .017, p = .005), resistin ( R 2 = .011, p = .012), monocyte ( R 2 = .027, p = .001), eosinophil ( R 2 = .012, p = .01) and basophil ( R 2 = .015, p = .002) levels in males, and a greater variance in concentrations of C3 ( R 2 = .175, p = .001), IL‐6 ( R 2 = .090, p = .001), TNF‐α ( R 2 = .036, p = .001), adiponectin ( R 2 = .121, p = .001), the adiponectin‐to‐leptin ratio ( R 2 = .444, p = .001), resistin ( R 2 = .025, p = .001), white blood cell count ( R 2 = .057, p = .001), neutrophils ( R 2 = .061, p = .001) and lymphocytes ( R 2 = .020, p = .001) in females. Conclusion Equations for assessing VAT levels might be useful to characterise metabolic health. Further studies that examine predicted VAT relationships with disease and mortality outcomes are warranted.
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Millar et al. (2023) reported a cross-sectional. Predicted visceral adipose tissue (VAT) equations vs. Anthropometric measures was evaluated on Variance in inflammatory biomarkers. Predicted visceral adipose tissue equations explained a greater proportion of variance in inflammatory biomarkers, such as CRP (R2=0.075, p=0.001 in males), compared with anthropometric measures.
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